Features on semiconductor devices and transmitters of optical fiber links are being formed that are less than one micron in width. Measurement of these sub-micron features is increasingly difficult as the size of the features become smaller. However, knowledge of the dimensions of gratings or periodic structures is essential in order to determine if the dimensions of the features are within the acceptable ranges and if a particular fabrication process causes the sidewalls of the features to be tapered, vertical, T-topped or undercut.
Traditionally, a sample is cleaved and examined with a scanning electron microscope or similar device. This method is slow and expensive. Angular scatterometry has been employed to measure linewidths of gratings, but the process requires a setup of multiple detectors at different angles from the incident beam to measure the diffraction of the scattered light. Again, this is difficult to implement because of the setup required. Another form of angular scatterometry, which only uses zeroth order light, is not very sensitive to sub-100 nm features due to the large wavelength of light typically used by the lasers used in the process.
Spectroscopic reflectometry and ellipsometry are used to direct light on the grating and measure the spectra of reflected signals. Current practices generally use an empirical approach where the spectra of reflected light is measured for a known width of features in a grating. This process is time consuming and expensive even for a limited library of profiles of grating dimensions and the associated spectrum data of reflected light. In another practice, libraries storing large numbers of profiles and signal data need to be built in advance, which requires large upfront processing times and, even then, cover only limited parameter ranges and resolutions. In another practice, real-time regression is used. However, this method covers only a limited parameter range due to the “real-time” nature that limits the amount of time available for simulation and search. In addition, unlike the library approach, a strict real-time regression method does not cover the result space comprehensively, potentially leaving the method mired in local minima, versus properly determining the global minimum.
Thus, there is a need for a less laborious and less expensive method of creating the library of profiles and associated spectrum data. There is also a need for a method and system of creating a dynamic library of grating profiles without first generating a master library, thereby obtaining more rapid searches, exhaustive coverage, and limited or zero upfront processing times.